Package specific_analyses :: Package frame_order :: Module parameters
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Module parameters

source code

Module for handling the frame order model parameters.

Functions [hide private]
numpy rank-1 array
assemble_param_vector(sim_index=None, unset_fail=False)
Assemble and return the parameter vector.
source code
numpy rank-2 NxM array, numpy rank-1 N array
linear_constraints(scaling_matrix=None)
Create the linear constraint matrices A and b.
source code
int
param_num()
Determine the number of parameters in the model.
source code
 
update_model(verbosity=1)
Update the model parameters as necessary.
source code
Variables [hide private]
  __package__ = 'specific_analyses.frame_order'

Imports: pi, array, float64, zeros, RelaxError, MODEL_DOUBLE_ROTOR, MODEL_FREE_ROTOR, MODEL_ISO_CONE, MODEL_ISO_CONE_FREE_ROTOR, MODEL_ISO_CONE_TORSIONLESS, MODEL_LIST_FREE_ROTORS, MODEL_LIST_ISO_CONE, MODEL_LIST_PSEUDO_ELLIPSE, MODEL_PSEUDO_ELLIPSE, MODEL_ROTOR, unique_elements, pivot_fixed


Function Details [hide private]

assemble_param_vector(sim_index=None, unset_fail=False)

source code 

Assemble and return the parameter vector.

Parameters:
  • sim_index (int) - The Monte Carlo simulation index.
  • unset_fail (bool) - A flag which if True will cause a RelaxError to be raised if the parameter is not set yet.
Returns: numpy rank-1 array
The parameter vector.

linear_constraints(scaling_matrix=None)

source code 

Create the linear constraint matrices A and b.

Standard notation

The parameter constraints for the motional amplitude parameters are:

   0 <= theta <= pi,
   0 <= theta_x <= theta_y <= pi,
   -0.125 <= S <= 1,
   0 <= sigma_max <= pi,

The pivot point and average domain position parameter constraints are:

   -999 <= pivot_x <= 999
   -999 <= pivot_y <= 999
   -999 <= pivot_z <= 999
   -500 <= ave_pos_x <= 500
   -500 <= ave_pos_y <= 500
   -500 <= ave_pos_y <= 500

These are necessary to allow for valid PDB representations to be created. The eigenframe parameters are unconstrained.

Matrix notation

In the notation A.x >= b, where A is an matrix of coefficients, x is an array of parameter values, and b is a vector of scalars, these inequality constraints are:

   | 1  0  0  0 |                        |   0    |
   |            |                        |        |
   |-1  0  0  0 |                        |  -pi   |
   |            |                        |        |
   | 0  1  0  0 |                        |   0    |
   |            |     |   theta   |      |        |
   | 0 -1  0  0 |     |           |      |  -pi   |
   |            |     |  theta_x  |      |        |
   | 0 -1  1  0 |  .  |           |  >=  |   0    |
   |            |     |  theta_y  |      |        |
   | 0  0  1  0 |     |           |      |   0    |
   |            |     | sigma_max |      |        |
   | 0  0 -1  0 |                        |  -pi   |
   |            |                        |        |
   | 0  0  0  1 |                        |   0    |
   |            |                        |        |
   | 0  0  0 -1 |                        |  -pi   |

The pivot and average position constraints in the A.x >= b notation are:

   | 1  0  0  0  0  0 |                        | -999.0 |
   |                  |                        |        |
   |-1  0  0  0  0  0 |                        | -999.0 |
   |                  |                        |        |
   | 0  1  0  0  0  0 |                        | -999.0 |
   |                  |                        |        |
   | 0 -1  0  0  0  0 |     |  pivot_x  |      | -999.0 |
   |                  |     |           |      |        |
   | 0  0  1  0  0  0 |     |  pivot_y  |      | -999.0 |
   |                  |     |           |      |        |
   | 0  0 -1  0  0  0 |     |  pivot_z  |      | -999.0 |
   |                  |  .  |           |  >=  |        |
   | 0  0  0  1  0  0 |     | ave_pos_x |      | -500.0 |
   |                  |     |           |      |        |
   | 0  0  0 -1  0  0 |     | ave_pos_y |      | -500.0 |
   |                  |     |           |      |        |
   | 0  0  0  0  1  0 |     | ave_pos_z |      | -500.0 |
   |                  |                        |        |
   | 0  0  0  0 -1  0 |                        | -500.0 |
   |                  |                        |        |
   | 0  0  0  0  0  1 |                        | -500.0 |
   |                  |                        |        |
   | 0  0  0  0  0 -1 |                        | -500.0 |
Parameters:
  • scaling_matrix (numpy rank-2 square matrix) - The diagonal, square scaling matrix.
Returns: numpy rank-2 NxM array, numpy rank-1 N array
The matrices A and b.

param_num()

source code 

Determine the number of parameters in the model.

Returns: int
The number of model parameters.

update_model(verbosity=1)

source code 

Update the model parameters as necessary.

Parameters:
  • verbosity (int) - If this value is greater than zero, then a number of printouts will occur.